Part 1: Rejecting null is not enough, also need estimate and precision. Bayesian estimation supersedes confidence intervals and "the new statistics".
Part 2: Two Bayesian ways to assess a null value. Highest density interval with region of practical equivalence. Bayesian model comparison and Bayes factor.
Part 3: Biased estimation in sequential testing and optional stopping.
Part 4: Monte Carlo study of biased estimation in sequential testing and optional stopping.
Parts 3 and 4 are elaborations of this previous blog post.